ArticleJournal of forensic sciences2026
Postmortem submergence interval (PMSI) and human decomposition in anthropogenically constructed aqueous environments (pools, bathtubs, hot tubs, and spas).
Article in Journal of forensic sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Postmortem submergence interval (PMSI) and human decomposition in anthropogenically constructed aqueous environments (pools, bathtubs, hot tubs, and spas).Journal of forensic sciences · 2026Article
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Authors and funding
5 authors.
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Abstract
Postmortem decomposition changes of bodies in aquatic environments may offer valuable insights into the postmortem submergence interval (PMSI) for medicolegal death investigators. However, the effects of immersion on the onset of such changes are poorly understood. The aims of this study were to augment what is known about the statistical relationship between PMSI and observable decomposition changes across three body regions (head, torso, and limbs) and to quantify the influence of extrinsic (e.g., clothing, immersion, location, and body position) and intrinsic (e.g., height, weight, BMI) moderating covariates for bodies in aqueous anthropogenically constructed environments. This study retrospectively examined 79 deceased adults recovered from pools, bathtubs, hot tubs, and spas between January 2010 and December 2019 in Victoria, Australia. Mean estimated PMSI was 18.33 h (SE = 3.83), and bivariate t-tests and ANOVA showed that PMSI was significantly related to gaseous distension of the face and torso, discoloration of the skin, marbling, skin sloughing, and discoloration of the torso and limbs. Univariate GLM (two-way factorial ANOVA) results showed that each moderating factor had a unique profile of influence on the various relationships between PMSI and the decomposition change being evaluated. Multiple linear regression modeling demonstrated the importance of including only specific moderators in estimations of PMSI. One model predicted nearly two-thirds of the variance in PMSI (adjusted R
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